Nonlinear electron devices, circuits, and systems represent a paradigm shift beyond traditional linear electronics, positioning themselves at the forefront of modern technological breakthroughs. Their unique behaviors are enabling radical advancements in next-generation computing, ultra-fast communications, and highly efficient neuromorphic engineering. This Research Topic is dedicated to exploring the latest theoretical and practical trends within this dynamic field, with a particular emphasis on memristive technologies.
Memristors, as a key element in resistive switching and nonvolatile memory, are revolutionizing brain-inspired computing architectures. Their inherent nonlinear dynamics and memory-dependent properties, which mimic synaptic plasticity, offer unprecedented opportunities for creating novel analog and digital systems that are both energy-efficient and powerful.
Beyond memristors, this issue will cover a broader spectrum of nonlinear phenomena, including the controlled chaos of nonlinear oscillators for secure communications, the enhanced sensitivity of nonlinear sensors, and the adaptive intelligence of self-tuning circuits. A core objective is to bridge the critical gap between theoretical models, numerical simulations, and tangible applications. We aim to highlight how intentional nonlinearity can be harnessed to create innovative technologies, ranging from reservoir computing and edge AI to ultra-low-power embedded systems. We therefore invite contributions that address novel device architectures, groundbreaking computational paradigms, and rigorous experimental validations to collectively advance the field toward scalable, efficient, and intelligent nonlinear electronic systems.
We welcome researchers and engineers from academia and industry to share their insights on the challenges and opportunities in this rapidly evolving domain, fostering the interdisciplinary collaboration necessary to drive future breakthroughs from theory to real-world impact.
We are looking for different kinds of contributions (original research, reviews, methods), related to the key topics of interest, which include, but are not limited to:
- Memristive devices: Modelling, fabrication, and applications in circuits, neuromorphic and in-memory computing - Emerging memory technologies: Resistive RAM (ReRAM), phase-change memory, and their nonlinear behaviour - Nonlinear dynamics in nanoscale devices: Quantum effects, stochastic behavior, and reliability challenges - Nonlinear sensors and actuators: Novel transduction mechanisms and adaptive sensing systems - Nonlinear circuits and chaos: Chaotic oscillators, secure communications, and nonlinear signal processing - Nonlinear circuits and systems for IoT and Edge Computing - Neuromorphic engineering: Bio-inspired systems, spiking neural networks, and adaptive learning - Machine learning with nonlinear devices: Hardware acceleration and unconventional computing paradigms
Article types and fees
This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:
Brief Research Report
Data Report
Editorial
FAIR² Data
FAIR² DATA Direct Submission
Hypothesis and Theory
Methods
Mini Review
Opinion
Articles that are accepted for publication by our external editors following rigorous peer review incur a publishing fee charged to Authors, institutions, or funders.
Article types
This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:
Brief Research Report
Data Report
Editorial
FAIR² Data
FAIR² DATA Direct Submission
Hypothesis and Theory
Methods
Mini Review
Opinion
Original Research
Perspective
Review
Systematic Review
Technology and Code
Keywords: Nonlinear electron devices, electronic systems, machine learning
Important note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.